基于CMOS传感器的采摘机器人作业优化研究  

Research of Operation Optimization of Picking Robot Based on CMOS Sensor

作　　者：廖晓文 毛盼娣 Liao Xiaowen;Mao Pandi(Chongqing Meropolitan College of Science and Technology,Chongqing 402167,China)

机构地区：[1]重庆城市科技学院,重庆402167

出　　处：《农机化研究》2024年第11期140-143,161,共5页Journal of Agricultural Mechanization Research

基　　金：重庆教育科学“十三五”规划2019年度重点课题(2019-GX-151);重庆市教委科学技术研究项目(KJQN202002501);重庆市高等教育教学改革研究项目(213473)。

摘　　要：针对传统的人工采摘方式危险系数高、效率低、劳动强度大的缺点,基于CMOS传感器对采摘机器人的作业过程进行了优化设计。采摘机器人分为视觉信息获取层、信息处理层和动作执行层,为了获取待采摘果蔬的准确位置,在CMOS摄像机完成图像的采集后,采用BP神经网络对摄像机进行标定,再利用NDI模型对图像进行预处理,提取图像有用特征。为了验证采摘机器人的性能,对其进行果蔬识别试验和距离测量试验,结果表明:采摘机器人对果蔬的识别效果良好,且确定的质心坐标误差满足采摘要求。Aiming at the problem of traditional manual picking method,such as high risk coefficient,low efficiency and high labor intensity,the operation process of the picking robot was optimized and studied based on CMOS sensor.The robot was constituted of information acquisition layer,information processing layer and action execution layer.To obtain the exact location of fruits and vegetables to be picked,after image acquisition by CMOS camera,BP neural network was used to calibrate the camera,and then NDI model was used to preprocess the image to extract the useful features of the image.To verify the performance of the picking robot,fruit and vegetables identification test and distance weight measurement experiment were carried out.The test results show that the picking robot has a good recognition effect on fruits and vegetables,and the determined centroid coordinate error meets the requirements of the picking robot.

关 键 词：采摘机器人 CMOS传感器 作业优化 BP神经网络 NDI模型 

分 类 号：S225[农业科学—农业机械化工程] TP242[农业科学—农业工程]